Bitbroker is a proof of concept for transaction visualization. We have a set of players and a sequence of transactions in time. A transaction can involve money, or energy, or anything that can be represented by a number and therefore, accumulated. All these transactions or events are located in time and represented as a timeline in the bottom of the window. Over this time line we draw a time window. This selects the time range in which the transactions will be drawn. The idea is to move and resize this time window to explore over all the recorded events.

The players or participants in the transactions are put in a circle. Each one is assigned a sector of the circle based on its “importance”, which is assigned “a priori”. The radius (or height) of the sector shows us the balance or accumulated “value” of every player. All of them start with a zero balance which evolves in time as we move the time window.

Transactions are drawn as curves from one player in the circle to another. The thickness of the curve is related to the amount of the transaction. Bigger transactions get thicker curves. We use the colors to show the direction of the movement (from orange to blue), which is coherent with the color code we use for the players in the circle. Only those transactions that fall within the time window are shown as curves in the circle.

This kind of representation can be useful to explore market transactions (share movements), money exchange between poker players, import and export among countries or any other interaction. This is just a generic demo.

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With this visualizer we inaugurate our python framework which is being released under GPL. It intensively uses numpy and OpenGL. This framework is still far from “ready”, but we are working on it and its documentation to get some criticism and maybe participation from others. You can get the code and instructions from the project hosted at google code here or directly download precompiled binaries from this link But we still recommend to read the document. If you don’t have the time to try this, just watch the video above.

Today the new Scopia’s blog is open!

You can follow the new products, the development of some experiments and more in the Scopia’s blog. Data.scopia, Plan9, the Fricker’s return, and the graphic products of our 3D department.

We wait you there!

Until now we had represented several RSS’s from some news sites. In this case we use a graph to navigate through the British museum’s objects. In this Graph there are three different node types: objects, rooms and Tours; and sorted by two relation types: theme and situation.

Click on the image below to execute it or here to edit.

You can view two new tutorials in the wiki section. Create your own graph with the data from the source you want, follow the tutorials and get it.

English - Building a simple graph

English - Building a Graph with different nodes

Spanish - Creación de un Grafo simple

Spanish - Creación de un grafo con nodos de distintos campos

Visualcomplexity.com is a website that gathers great visualization projects all around the Internet. We submitted our project there and they have finally made a review of it. It is very nice to have a little place on their site. You can see the review here. And we appear in the latest projects list on the frontpage. Thank you guys!

We have added a background image in this Graph. In the Show Graph Block you can find the Background Image field. You only have to write the URL to an image and then you got it. The graph’s source comes from a programame.net’s RSS, a site with a system similar to meneame but adressed to developers (in spanish )

Click on the image below to execute the macro

In the same way as the “meneame graph” that has been already published, now we suggest you a new graph from Dzone.com. Just by clicking on the node label, you can obtain full information about the elements, and also a thumbnail image from the realated web.

Click on the image below to execute the macro

Tagged collections are best handled as graphs, but digg is different. It has exclusive categories. All articles are stored in a two-level tree. First you have the main categories, then the subcategories and finally the articles. So we have thought that the best tool we have to handle all this tagged collections is our tree map. Now, a new public Macro is available for you to browse digg published news as a tree map. Click on the image below.

Remember to go down the tree with the arrows or by clicking on the boxes.

Unfortunately, digg rss feed only gives the subcategory for each item. In order to classify them, using the main categories, we have made an external spreadsheet with a list of the items, and we have added the relationships with the different subcategories.

You can have a look at the spreadsheet clicking here, then you will be able to verify that it can also be used to assign colors to the different boxes. To execute the Macro we just do a “join” operation with the rss feed to expand the information for each item.

Enjoy it!

You can visit us at http://macro.scopia.es

We have already seen listings and treemaps at Macro.Scopia. But now It allows you to plot the data as a graph, with nodes showing elements and arcs showing relationships. It could be very useful to plot tagged elements, like articles from a blog or any other dinamic webs.

The purpose of this new Macro view is to show a few connected elements at the beggining, and then let you navigate by clicking on the nodes you are interested in. Full information about the elements can be seen just by clicking on the label of the nodes.

In order to show you the capabilities of this Macro, we have made a view of the current news posted at